Method for analyzing heart rate variability, apparatus and use thereof
a heart rate variability and analysis method technology, applied in the field of methods and apparatus for analyzing heart rate variability, can solve the problems of large individual differences in efficacy of drug treatment, high uncertainty, and patient resistance to drug treatment, and achieve efficient screening, save unnecessary expenditures, and accurate results
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example 1
[0040]As shown in FIG. 2, a standard 12-lead ECG acquisition for 24 hours before surgery requires: sampling frequency of the ECG acquisition device is greater than or equal to 500 Hz; during ECG recording, activities such as strenuous exercises and medications that could affect cardiac functions should be avoided; the recording period is 24 hours. Recording environment and conditions of subjects should be basically similar. The data used for HRV analysis should be ensured to be normal sinus NN intervals. During HRV analysis, normal sinus NN intervals of 4 hours are selected for MSE analysis from the 24-hour long-term ECG records during which the subject is in an awake state. The specific processing flow of ECG signals is shown in FIG. 3.
[0041]1) collecting and digitizing ECG signals;
[0042]2) denoising and de-articulating digital signals;
[0043]3) automatically detecting QRS waves thereof;
[0044]4) manually inspecting QRS waves of the detected signals;
[0045]5) removing ectopic exciting...
example 2
[0063]The complexity indicator Area 6-n, when the scale factor in the MES analysis method of Example 1 is expanded to n, could also be used for screening VNS patients as described above.
[0064]In the present invention, for patients with drug refractory epilepsy, preoperative electrocardiogram acquisition 24 hours before surgery and the MSE analysis of HRV were performed. In this way, patients with drug refractory epilepsy could be screened before surgery, thereby guiding patients who are not eligible for VNS therapy not to receive the surgery and choose other therapies, which could save unnecessary expenditures and avoiding delaying the optimal timing for treatment. Meanwhile, patients with VNS surgical indications were clearly selected by extracting characteristic parameters representing heart rate complexity through ECG's MSE curve, which could improve overall VNS therapeutic efficacy.
example 3
[0065]In accordance with the above screening method, 32 patients with medical refractory epilepsy, who had undergone VNS surgery at Beijing Tiantan Hospital from Aug. 13, 2014 to Dec. 31, 2014, were selected for test. Before VNS surgery, these 32 patients with medical refractory epilepsy were comprehensively evaluated (including demographic characteristics, clinical history, history of antiepileptic medication, 24-hours video-EEG, MRI, and 24-hour dynamic electrocardiogram etc.).
[0066]According to the above ECG signal processing method, the MSE analysis was performed, based on 24-hour dynamic electrocardiographic data. The corresponding characteristic parameters Slope5, Area1-5, Area6-15, and Area6-20 were extracted based on each patient's MSE curve. At the end of 1-year follow-up, among 32 patients with drug refractory epilepsy who had undergone VNS treatment, 28 patients' seizure frequencies had been reduced to various degrees (seizures had been completely controlled in 6 patients...
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